// Copyright 2021 The Prometheus Authors // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. //go:build go1.17 // +build go1.17 package prometheus import ( "fmt" "math" "runtime" "runtime/metrics" "strings" "sync" "github.com/prometheus/client_golang/prometheus/internal" dto "github.com/prometheus/client_model/go" "google.golang.org/protobuf/proto" ) const ( // constants for strings referenced more than once. goGCGogcPercent = "/gc/gogc:percent" goGCHeapTinyAllocsObjects = "/gc/heap/tiny/allocs:objects" goGCHeapAllocsObjects = "/gc/heap/allocs:objects" goGCHeapFreesObjects = "/gc/heap/frees:objects" goGCHeapFreesBytes = "/gc/heap/frees:bytes" goGCHeapAllocsBytes = "/gc/heap/allocs:bytes" goGCHeapObjects = "/gc/heap/objects:objects" goGCHeapGoalBytes = "/gc/heap/goal:bytes" goGCMemLimit = "/gc/gomemlimit:bytes" goMemoryClassesTotalBytes = "/memory/classes/total:bytes" goMemoryClassesHeapObjectsBytes = "/memory/classes/heap/objects:bytes" goMemoryClassesHeapUnusedBytes = "/memory/classes/heap/unused:bytes" goMemoryClassesHeapReleasedBytes = "/memory/classes/heap/released:bytes" goMemoryClassesHeapFreeBytes = "/memory/classes/heap/free:bytes" goMemoryClassesHeapStacksBytes = "/memory/classes/heap/stacks:bytes" goMemoryClassesOSStacksBytes = "/memory/classes/os-stacks:bytes" goMemoryClassesMetadataMSpanInuseBytes = "/memory/classes/metadata/mspan/inuse:bytes" goMemoryClassesMetadataMSPanFreeBytes = "/memory/classes/metadata/mspan/free:bytes" goMemoryClassesMetadataMCacheInuseBytes = "/memory/classes/metadata/mcache/inuse:bytes" goMemoryClassesMetadataMCacheFreeBytes = "/memory/classes/metadata/mcache/free:bytes" goMemoryClassesProfilingBucketsBytes = "/memory/classes/profiling/buckets:bytes" goMemoryClassesMetadataOtherBytes = "/memory/classes/metadata/other:bytes" goMemoryClassesOtherBytes = "/memory/classes/other:bytes" goSchedMaxProcs = "/sched/gomaxprocs:threads" ) // rmNamesForMemStatsMetrics represents runtime/metrics names required to populate goRuntimeMemStats from like logic. var rmNamesForMemStatsMetrics = []string{ goGCHeapTinyAllocsObjects, goGCHeapAllocsObjects, goGCHeapFreesObjects, goGCHeapAllocsBytes, goGCHeapObjects, goGCHeapGoalBytes, goMemoryClassesTotalBytes, goMemoryClassesHeapObjectsBytes, goMemoryClassesHeapUnusedBytes, goMemoryClassesHeapReleasedBytes, goMemoryClassesHeapFreeBytes, goMemoryClassesHeapStacksBytes, goMemoryClassesOSStacksBytes, goMemoryClassesMetadataMSpanInuseBytes, goMemoryClassesMetadataMSPanFreeBytes, goMemoryClassesMetadataMCacheInuseBytes, goMemoryClassesMetadataMCacheFreeBytes, goMemoryClassesProfilingBucketsBytes, goMemoryClassesMetadataOtherBytes, goMemoryClassesOtherBytes, } var rmNamesForEnvVarsMetrics = []string{ // how to name this var??? goGCGogcPercent, goGCMemLimit, goSchedMaxProcs, } func bestEffortLookupRM(lookup []string) []metrics.Description { ret := make([]metrics.Description, 0, len(lookup)) for _, rm := range metrics.All() { for _, m := range lookup { if m == rm.Name { ret = append(ret, rm) } } } return ret } type goCollector struct { base baseGoCollector // mu protects updates to all fields ensuring a consistent // snapshot is always produced by Collect. mu sync.Mutex // Contains all samples that has to retrieved from runtime/metrics (not all of them will be exposed). sampleBuf []metrics.Sample // sampleMap allows lookup for MemStats metrics and runtime/metrics histograms for exact sums. sampleMap map[string]*metrics.Sample // rmExposedMetrics represents all runtime/metrics package metrics // that were configured to be exposed. rmExposedMetrics []collectorMetric rmExactSumMapForHist map[string]string // With Go 1.17, the runtime/metrics package was introduced. // From that point on, metric names produced by the runtime/metrics // package could be generated from runtime/metrics names. However, // these differ from the old names for the same values. // // This field exists to export the same values under the old names // as well. msMetrics memStatsMetrics msMetricsEnabled bool rmEnvVarsMetrics runtimeEnvVarsMetrics // how to call them??? rmEnvVarsMetricsEnabled bool } type rmMetricDesc struct { metrics.Description } func matchRuntimeMetricsRules(rules []internal.GoCollectorRule) []rmMetricDesc { var descs []rmMetricDesc for _, d := range metrics.All() { var ( deny = true desc rmMetricDesc ) for _, r := range rules { if !r.Matcher.MatchString(d.Name) { continue } deny = r.Deny } if deny { continue } desc.Description = d descs = append(descs, desc) } return descs } func defaultGoCollectorOptions() internal.GoCollectorOptions { return internal.GoCollectorOptions{ RuntimeMetricSumForHist: map[string]string{ "/gc/heap/allocs-by-size:bytes": goGCHeapAllocsBytes, "/gc/heap/frees-by-size:bytes": goGCHeapFreesBytes, }, RuntimeMetricRules: []internal.GoCollectorRule{ //{Matcher: regexp.MustCompile("")}, }, } } // NewGoCollector is the obsolete version of collectors.NewGoCollector. // See there for documentation. // // Deprecated: Use collectors.NewGoCollector instead. func NewGoCollector(opts ...func(o *internal.GoCollectorOptions)) Collector { opt := defaultGoCollectorOptions() for _, o := range opts { o(&opt) } exposedDescriptions := matchRuntimeMetricsRules(opt.RuntimeMetricRules) // Collect all histogram samples so that we can get their buckets. // The API guarantees that the buckets are always fixed for the lifetime // of the process. var histograms []metrics.Sample for _, d := range exposedDescriptions { if d.Kind == metrics.KindFloat64Histogram { histograms = append(histograms, metrics.Sample{Name: d.Name}) } } if len(histograms) > 0 { metrics.Read(histograms) } bucketsMap := make(map[string][]float64) for i := range histograms { bucketsMap[histograms[i].Name] = histograms[i].Value.Float64Histogram().Buckets } // Generate a collector for each exposed runtime/metrics metric. metricSet := make([]collectorMetric, 0, len(exposedDescriptions)) // SampleBuf is used for reading from runtime/metrics. // We are assuming the largest case to have stable pointers for sampleMap purposes. sampleBuf := make([]metrics.Sample, 0, len(exposedDescriptions)+len(opt.RuntimeMetricSumForHist)+len(rmNamesForMemStatsMetrics)+len(rmNamesForEnvVarsMetrics)) sampleMap := make(map[string]*metrics.Sample, len(exposedDescriptions)) for _, d := range exposedDescriptions { namespace, subsystem, name, ok := internal.RuntimeMetricsToProm(&d.Description) if !ok { // Just ignore this metric; we can't do anything with it here. // If a user decides to use the latest version of Go, we don't want // to fail here. This condition is tested in TestExpectedRuntimeMetrics. continue } sampleBuf = append(sampleBuf, metrics.Sample{Name: d.Name}) sampleMap[d.Name] = &sampleBuf[len(sampleBuf)-1] var m collectorMetric if d.Kind == metrics.KindFloat64Histogram { _, hasSum := opt.RuntimeMetricSumForHist[d.Name] unit := d.Name[strings.IndexRune(d.Name, ':')+1:] m = newBatchHistogram( NewDesc( BuildFQName(namespace, subsystem, name), d.Description.Description, nil, nil, ), internal.RuntimeMetricsBucketsForUnit(bucketsMap[d.Name], unit), hasSum, ) } else if d.Cumulative { m = NewCounter(CounterOpts{ Namespace: namespace, Subsystem: subsystem, Name: name, Help: d.Description.Description, }, ) } else { m = NewGauge(GaugeOpts{ Namespace: namespace, Subsystem: subsystem, Name: name, Help: d.Description.Description, }) } metricSet = append(metricSet, m) } // Add exact sum metrics to sampleBuf if not added before. for _, h := range histograms { sumMetric, ok := opt.RuntimeMetricSumForHist[h.Name] if !ok { continue } if _, ok := sampleMap[sumMetric]; ok { continue } sampleBuf = append(sampleBuf, metrics.Sample{Name: sumMetric}) sampleMap[sumMetric] = &sampleBuf[len(sampleBuf)-1] } var ( msMetrics memStatsMetrics msDescriptions []metrics.Description rmEnvVarsMetrics runtimeEnvVarsMetrics rmEnvVarsDescriptions []metrics.Description ) if !opt.DisableMemStatsLikeMetrics { msMetrics = goRuntimeMemStats() msDescriptions = bestEffortLookupRM(rmNamesForMemStatsMetrics) // Check if metric was not exposed before and if not, add to sampleBuf. for _, mdDesc := range msDescriptions { if _, ok := sampleMap[mdDesc.Name]; ok { continue } sampleBuf = append(sampleBuf, metrics.Sample{Name: mdDesc.Name}) sampleMap[mdDesc.Name] = &sampleBuf[len(sampleBuf)-1] } } if !opt.DisableRuntimeEnvVarsMetrics { rmEnvVarsMetrics = goRuntimeEnvVarsMetrics() rmEnvVarsDescriptions = bestEffortLookupRM(rmNamesForEnvVarsMetrics) // Check if metric was not exposed before and if not, add to sampleBuf. for _, rnevDesc := range rmEnvVarsDescriptions { if _, ok := sampleMap[rnevDesc.Name]; ok { continue } sampleBuf = append(sampleBuf, metrics.Sample{Name: rnevDesc.Name}) sampleMap[rnevDesc.Name] = &sampleBuf[len(sampleBuf)-1] } } return &goCollector{ base: newBaseGoCollector(), sampleBuf: sampleBuf, sampleMap: sampleMap, rmExposedMetrics: metricSet, rmExactSumMapForHist: opt.RuntimeMetricSumForHist, msMetrics: msMetrics, msMetricsEnabled: !opt.DisableMemStatsLikeMetrics, rmEnvVarsMetrics: rmEnvVarsMetrics, rmEnvVarsMetricsEnabled: !opt.DisableRuntimeEnvVarsMetrics, } } // Describe returns all descriptions of the collector. func (c *goCollector) Describe(ch chan<- *Desc) { c.base.Describe(ch) for _, i := range c.msMetrics { ch <- i.desc } for _, m := range c.rmExposedMetrics { ch <- m.Desc() } } // Collect returns the current state of all metrics of the collector. func (c *goCollector) Collect(ch chan<- Metric) { // Collect base non-memory metrics. c.base.Collect(ch) if len(c.sampleBuf) == 0 { return } // Collect must be thread-safe, so prevent concurrent use of // sampleBuf elements. Just read into sampleBuf but write all the data // we get into our Metrics or MemStats. // // This lock also ensures that the Metrics we send out are all from // the same updates, ensuring their mutual consistency insofar as // is guaranteed by the runtime/metrics package. // // N.B. This locking is heavy-handed, but Collect is expected to be called // relatively infrequently. Also the core operation here, metrics.Read, // is fast (O(tens of microseconds)) so contention should certainly be // low, though channel operations and any allocations may add to that. c.mu.Lock() defer c.mu.Unlock() // Populate runtime/metrics sample buffer. metrics.Read(c.sampleBuf) // Collect all our runtime/metrics user chose to expose from sampleBuf (if any). for i, metric := range c.rmExposedMetrics { // We created samples for exposed metrics first in order, so indexes match. sample := c.sampleBuf[i] // N.B. switch on concrete type because it's significantly more efficient // than checking for the Counter and Gauge interface implementations. In // this case, we control all the types here. switch m := metric.(type) { case *counter: // Guard against decreases. This should never happen, but a failure // to do so will result in a panic, which is a harsh consequence for // a metrics collection bug. v0, v1 := m.get(), unwrapScalarRMValue(sample.Value) if v1 > v0 { m.Add(unwrapScalarRMValue(sample.Value) - m.get()) } m.Collect(ch) case *gauge: m.Set(unwrapScalarRMValue(sample.Value)) m.Collect(ch) case *batchHistogram: m.update(sample.Value.Float64Histogram(), c.exactSumFor(sample.Name)) m.Collect(ch) default: panic("unexpected metric type") } } if c.msMetricsEnabled { // ms is a dummy MemStats that we populate ourselves so that we can // populate the old metrics from it if goMemStatsCollection is enabled. var ms runtime.MemStats memStatsFromRM(&ms, c.sampleMap) for _, i := range c.msMetrics { ch <- MustNewConstMetric(i.desc, i.valType, i.eval(&ms)) } } if c.rmEnvVarsMetricsEnabled { sampleBuf := make([]metrics.Sample, len(c.rmEnvVarsMetrics)) for i, v := range c.rmEnvVarsMetrics { sampleBuf[i].Name = v.origMetricName } metrics.Read(sampleBuf) for i, v := range c.rmEnvVarsMetrics { ch <- MustNewConstMetric(v.desc, GaugeValue, unwrapScalarRMValue(sampleBuf[i].Value)) } } } // unwrapScalarRMValue unwraps a runtime/metrics value that is assumed // to be scalar and returns the equivalent float64 value. Panics if the // value is not scalar. func unwrapScalarRMValue(v metrics.Value) float64 { switch v.Kind() { case metrics.KindUint64: return float64(v.Uint64()) case metrics.KindFloat64: return v.Float64() case metrics.KindBad: // Unsupported metric. // // This should never happen because we always populate our metric // set from the runtime/metrics package. panic("unexpected bad kind metric") default: // Unsupported metric kind. // // This should never happen because we check for this during initialization // and flag and filter metrics whose kinds we don't understand. panic(fmt.Sprintf("unexpected unsupported metric: %v", v.Kind())) } } // exactSumFor takes a runtime/metrics metric name (that is assumed to // be of kind KindFloat64Histogram) and returns its exact sum and whether // its exact sum exists. // // The runtime/metrics API for histograms doesn't currently expose exact // sums, but some of the other metrics are in fact exact sums of histograms. func (c *goCollector) exactSumFor(rmName string) float64 { sumName, ok := c.rmExactSumMapForHist[rmName] if !ok { return 0 } s, ok := c.sampleMap[sumName] if !ok { return 0 } return unwrapScalarRMValue(s.Value) } func memStatsFromRM(ms *runtime.MemStats, rm map[string]*metrics.Sample) { lookupOrZero := func(name string) uint64 { if s, ok := rm[name]; ok { return s.Value.Uint64() } return 0 } // Currently, MemStats adds tiny alloc count to both Mallocs AND Frees. // The reason for this is because MemStats couldn't be extended at the time // but there was a desire to have Mallocs at least be a little more representative, // while having Mallocs - Frees still represent a live object count. // Unfortunately, MemStats doesn't actually export a large allocation count, // so it's impossible to pull this number out directly. tinyAllocs := lookupOrZero(goGCHeapTinyAllocsObjects) ms.Mallocs = lookupOrZero(goGCHeapAllocsObjects) + tinyAllocs ms.Frees = lookupOrZero(goGCHeapFreesObjects) + tinyAllocs ms.TotalAlloc = lookupOrZero(goGCHeapAllocsBytes) ms.Sys = lookupOrZero(goMemoryClassesTotalBytes) ms.Lookups = 0 // Already always zero. ms.HeapAlloc = lookupOrZero(goMemoryClassesHeapObjectsBytes) ms.Alloc = ms.HeapAlloc ms.HeapInuse = ms.HeapAlloc + lookupOrZero(goMemoryClassesHeapUnusedBytes) ms.HeapReleased = lookupOrZero(goMemoryClassesHeapReleasedBytes) ms.HeapIdle = ms.HeapReleased + lookupOrZero(goMemoryClassesHeapFreeBytes) ms.HeapSys = ms.HeapInuse + ms.HeapIdle ms.HeapObjects = lookupOrZero(goGCHeapObjects) ms.StackInuse = lookupOrZero(goMemoryClassesHeapStacksBytes) ms.StackSys = ms.StackInuse + lookupOrZero(goMemoryClassesOSStacksBytes) ms.MSpanInuse = lookupOrZero(goMemoryClassesMetadataMSpanInuseBytes) ms.MSpanSys = ms.MSpanInuse + lookupOrZero(goMemoryClassesMetadataMSPanFreeBytes) ms.MCacheInuse = lookupOrZero(goMemoryClassesMetadataMCacheInuseBytes) ms.MCacheSys = ms.MCacheInuse + lookupOrZero(goMemoryClassesMetadataMCacheFreeBytes) ms.BuckHashSys = lookupOrZero(goMemoryClassesProfilingBucketsBytes) ms.GCSys = lookupOrZero(goMemoryClassesMetadataOtherBytes) ms.OtherSys = lookupOrZero(goMemoryClassesOtherBytes) ms.NextGC = lookupOrZero(goGCHeapGoalBytes) // N.B. GCCPUFraction is intentionally omitted. This metric is not useful, // and often misleading due to the fact that it's an average over the lifetime // of the process. // See https://github.com/prometheus/client_golang/issues/842#issuecomment-861812034 // for more details. ms.GCCPUFraction = 0 } // batchHistogram is a mutable histogram that is updated // in batches. type batchHistogram struct { selfCollector // Static fields updated only once. desc *Desc hasSum bool // Because this histogram operates in batches, it just uses a // single mutex for everything. updates are always serialized // but Write calls may operate concurrently with updates. // Contention between these two sources should be rare. mu sync.Mutex buckets []float64 // Inclusive lower bounds, like runtime/metrics. counts []uint64 sum float64 // Used if hasSum is true. } // newBatchHistogram creates a new batch histogram value with the given // Desc, buckets, and whether or not it has an exact sum available. // // buckets must always be from the runtime/metrics package, following // the same conventions. func newBatchHistogram(desc *Desc, buckets []float64, hasSum bool) *batchHistogram { // We need to remove -Inf values. runtime/metrics keeps them around. // But -Inf bucket should not be allowed for prometheus histograms. if buckets[0] == math.Inf(-1) { buckets = buckets[1:] } h := &batchHistogram{ desc: desc, buckets: buckets, // Because buckets follows runtime/metrics conventions, there's // 1 more value in the buckets list than there are buckets represented, // because in runtime/metrics, the bucket values represent *boundaries*, // and non-Inf boundaries are inclusive lower bounds for that bucket. counts: make([]uint64, len(buckets)-1), hasSum: hasSum, } h.init(h) return h } // update updates the batchHistogram from a runtime/metrics histogram. // // sum must be provided if the batchHistogram was created to have an exact sum. // h.buckets must be a strict subset of his.Buckets. func (h *batchHistogram) update(his *metrics.Float64Histogram, sum float64) { counts, buckets := his.Counts, his.Buckets h.mu.Lock() defer h.mu.Unlock() // Clear buckets. for i := range h.counts { h.counts[i] = 0 } // Copy and reduce buckets. var j int for i, count := range counts { h.counts[j] += count if buckets[i+1] == h.buckets[j+1] { j++ } } if h.hasSum { h.sum = sum } } func (h *batchHistogram) Desc() *Desc { return h.desc } func (h *batchHistogram) Write(out *dto.Metric) error { h.mu.Lock() defer h.mu.Unlock() sum := float64(0) if h.hasSum { sum = h.sum } dtoBuckets := make([]*dto.Bucket, 0, len(h.counts)) totalCount := uint64(0) for i, count := range h.counts { totalCount += count if !h.hasSum { if count != 0 { // N.B. This computed sum is an underestimate. sum += h.buckets[i] * float64(count) } } // Skip the +Inf bucket, but only for the bucket list. // It must still count for sum and totalCount. if math.IsInf(h.buckets[i+1], 1) { break } // Float64Histogram's upper bound is exclusive, so make it inclusive // by obtaining the next float64 value down, in order. upperBound := math.Nextafter(h.buckets[i+1], h.buckets[i]) dtoBuckets = append(dtoBuckets, &dto.Bucket{ CumulativeCount: proto.Uint64(totalCount), UpperBound: proto.Float64(upperBound), }) } out.Histogram = &dto.Histogram{ Bucket: dtoBuckets, SampleCount: proto.Uint64(totalCount), SampleSum: proto.Float64(sum), } return nil }